Evaluation of image analysis software competency in skeletal muscle percentage assessment in meat products

نویسندگان
گروه بهداشت مواد غذایی، دانشکده دامپزشکی، دانشگاه بوعلی سینا، همدان، ایران
چکیده
In recent years, there has been a growing interest in methods for assessing the percentage of meat (skeletal muscle) in meat products. Given the high margin of error in methods such as chemical analysis, the most reliable and accurate approach for assessing the percentage of skeletal muscle in meat products is histology and subsequent use of image analysis. Due to limited research in this field and the not-so-easy access to some image analysis software, the present study, for the first time, examines the percentage of skeletal muscle in meat products and the time spent on analyzing each sample using two freely accessible graphic software programs (Adobe Photoshop and ImageJ) and two non-free graphic software programs (Clemex and Image Pro-Plus). For this purpose, 100 samples of meat products (30 Kielbasa, 30 sausages, 20 hamburgers, 10 kebab bite, and 10 chicken nuggets) with a known skeletal muscle content were used. After transferring the samples to the laboratory and preparing tissue sections using the Hematoxylin-Eosin staining method, the images of tissue sections were analyzed using the mentioned software programs. The results showed almost equal accuracy of all four software programs assessing skeletal muscles. However, the time required to analyze each ImageJ sample was significantly lower than the other software programs (p< 0.05). Based on the results of this study, it appears that ImageJ software offers greater competence for image analysis of tissue sections and determining the percentage of skeletal muscle in meat products.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Evaluation of image analysis software competency in skeletal muscle percentage assessment in meat products

نویسندگان English

Bahman Yarvari
Ali Kalantari-Hesari
Mohammadreza Pajohi alamoti
Mohammad Babaei
Department of Food Hygiene, Faculty of Veterinary Medicine, Bu-Ali Sina University, Hamedan, Iran
چکیده English

In recent years, there has been a growing interest in methods for assessing the percentage of meat (skeletal muscle) in meat products. Given the high margin of error in methods such as chemical analysis, the most reliable and accurate approach for assessing the percentage of skeletal muscle in meat products is histology and subsequent use of image analysis. Due to limited research in this field and the not-so-easy access to some image analysis software, the present study, for the first time, examines the percentage of skeletal muscle in meat products and the time spent on analyzing each sample using two freely accessible graphic software programs (Adobe Photoshop and ImageJ) and two non-free graphic software programs (Clemex and Image Pro-Plus). For this purpose, 100 samples of meat products (30 Kielbasa, 30 sausages, 20 hamburgers, 10 kebab bite, and 10 chicken nuggets) with a known skeletal muscle content were used. After transferring the samples to the laboratory and preparing tissue sections using the Hematoxylin-Eosin staining method, the images of tissue sections were analyzed using the mentioned software programs. The results showed almost equal accuracy of all four software programs assessing skeletal muscles. However, the time required to analyze each ImageJ sample was significantly lower than the other software programs (p< 0.05). Based on the results of this study, it appears that ImageJ software offers greater competence for image analysis of tissue sections and determining the percentage of skeletal muscle in meat products.

کلیدواژه‌ها English

Meat products
Histology
Image Analysis
Graphic Software
[1]. Asadi, M. R., Taghavi, M., Kalantari-Hesari, A., Ghorbanzadeh, B. The Role of Histological Test in Reducing the Use of Unauthorized Tissues in Meat Products Between Years of 2014 and 2017. Veterinary Researches & Biological Products. 2019; 33(3): 31-40 [In Persian].
[2]. Jahed, K. G. R., Rokni, N. Histological detection of soya in freezing raw hamburger of Iran. Pajouhesh and Sazandegi. 2004; 62: 71-75 [In Persian].
[3]. Kamkar, A., Rokny, N., Rasouli, A., Shiroudi, A. Evaluating hamburger quality using collagen content. Pajouhesh and Sazandegi. 2004; 63: 75-79 [In Persian].
[4]. Latorre, R., Sadeghinezhad, J., Hajimohammadi, B., Izadi, F., Sheibani, M. T. Application of Morphological Method for Detection of Unauthorized Tissues in Processed Meat Products. Journal of Food Quality and Hazards Control. 2015; 2(2): 71-74.
[5]. Rokni, N., Rezaeian, M., Nouri, N., Ebrahimpour, F. Detection of unauthorized tissues in some of the distributed raw meat products in Tehran with histological methods. Pajouhesh and Sazandegi. 2004; 17(4): 2-8 [In Persian].
[6]. Abbasy-Fasarani, M., Hosseini, H., Jahed-Khaniki, G. R., Adibmoradi, M., Eskandari, S. Histological study of industrial hamburgers containing 30 and 60 percent meat for presence of unpermitted edible tissues and correlation of this factor to meat connective tissue chemical indices. Iranian Journal of Nutrition Sciences & Food Technology. 2013; 7(5): 311-318 [In Persian].
[7]. Francisco, J. S., Moraes, H. P., Dias, E. P. Evaluation of the Image-Pro Plus 4.5 software for automatic counting of labeled nuclei by PCNA immunohistochemistry. Brazilian oral research. 2004; 18(2): 100-104.
[8]. Fernandes-Santos, C., Souza-Mello, V., Faria, S. T., Mandarim-De-Lacerda, C. A. Quantitative morphology update: Image analysis. International Journal of Morphology. 2013; 31(1): 23-30.
[9]. Bringhenti, I., Schultz, A. Rachid, T., Bomfim, M. A., Mandarimde- Lacerda, C. A., Aguila, M. B. An early fish oil-enriched diet reverses biochemical, liver, and adipose tissue alteration in male offspring from maternal protein restriction in mice. The Journal of Nutritional Biochemistry. 2011; 22(11): 1009-1014.
[10]. Fernandes-Santos, C., Carneiro, R. E., Mendonca, L. S., Aguila, M. B., Mandarim-de-Lacerda, C. A. Rosiglitazone aggravates nonalcoholic fatty pancreatic disease in C57BL/6 mice fed a high-fat and high-sucrose diet. Pancreas. 2009; 38(3): 80-86.
[11]. He, L., Long, L. R. Antani, S., Thoma, G. R. Histology image analysis for carcinoma detection and grading. Computer Methods and Programs in Biomedicine. 2012; 107(3): 538-556.
[12]. Ghisleni, G., Stella, S., Radaelli, E., Mattiello, S., Scanziani, E. Qualitative evaluation of tortellini meat filling by histology and image analysis. International Journal of Food Science and Technology. 2010; 45: 265–270.
[13]. Ash, N. F., Massengill, M. T., Harmer, L., Jafri, A., Lewin, A. S. Automated segmentation and analysis of retinal microglia within ImageJ. Experimental eye research. 2021; 203: 108416.
[14]. Jensen, E. C. Quantitative analysis of histological staining and fluorescence using ImageJ. The Anatomical Record. 2013; 296(3): 378-381.
[15]. Buchan, L., St Aubin, C. R., Fisher, A. L., Hellings, A., Castro, M., Al-Nakkash, L., Broderick, T. L. Plochocki JH. High-fat, high-sugar diet induces splenomegaly that is ameliorated with exercise and genistein treatment. BMC Research Notes. 2018; 11(1): 1-6.
[16]. Moraru, D., Istrate, S., Eniceicu, C. P., Sterian, P. Data analyses with ImageJ software in diabetic retinopathy, by processing the optical coherence tomography images. Journal of Clinical Review & Case Reports. 2020; 5: 34-39.
[17]. Taşdemir, U., Özeç, İ., Esen, H. H., Avunduk, M. C. The influence of rifamycin decontamination on the incorporation of autologous onlay bone grafts in rats: A histometric and immunohistochemical evaluation. Archives of Oral Biology. 2015; 60(5):724-729.
[18]. Seyhan, N., Keskin, S., Aktan, M., Avunduk, M. C., Sengelen, M., Savaci, N. Comparison of the effect of platelet-rich plasma and simvastatin on the healing of critical-size calvarial bone defects. Journal of Craniofacial Surgery. 2016; 27(5):1367-1370.
[19]. Saad, H. A., Terry, M. A., Shamie, N., Chen, E. S., Friend, D. F., Holiman, J. D., Stoeger, C. An easy and inexpensive method for quantitative analysis of endothelial damage by using vital dye staining and Adobe Photoshop software. Cornea. 2008; 27(7): 818-824.
[20]. Tolivia, J., Navarro, A., Valle, E. D., Perez, C., Ordonez, C., MartÌnez, E. Application of Photoshop and Scion Image analysis to quantification of signals in histochemistry, immunocytochemistry, and hybridocytochemistry. Analytical and Quantitative Cytology and Histology. 2006; 28(1): 43-53.
[21]. Agley, C. C., Velloso, C. P., Lazarus, N. R., Harridge, S. D. An image analysis method for the precise selection and quantitation of fluorescently labeled cellular constituents: application to the measurement of human muscle cells in culture. Journal of Histochemistry & Cytochemistry. 2012; 60(6):428-438.
[22]. Anderson, G., Bancroft, J. D. Tissue processing and microtomy. In: Theory and Practice of Histological Techniques (edited by J.D. Bancroft & M. Gamble). (8th. pp. 85–107). London: Churchill Livingstone. 2002.
[23]. Asadi, M. R., Kalantari-Hesari, A., Ghaemmaghami, S. S., Mosleh, N., Ghorbanzadeh, B., Abdi, P. Meat products components using histological method and image analysis software. Veterinary Research & Biological Products. 2023; 36(1): 102-112 [In Persian].